Abstract
eural Network (NN) is designed to detect QRS complex from ECG signal. QRS complex detection is essential so that RR-interval can be measured for disease classification and can also be monitoring the heart rate. In this paper, a supervised Neural Network based algorithm has been used to detect R in QRS complex. It was tried to find out the R-peak in QRS complex with missing peak and false peak as well, so that the correct decision can be made by the physician and clinician. The accuracy of finding the R-peak by using the Neural Network was 99.09% averagely and the average percentage of missing and false peak was 00.09%. The technique appears to be exceedingly robust, correctly detects R-peaks even aberrant QRS complexes in noise-corrupted ECGs.
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© 2008 Springer-Verlag Berlin Heidelberg
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Hasan, M.A., Ibrahimy, M.I., Reaz, M.B.I. (2008). NN-Based R-peak Detection in QRS Complex of ECG Signal. In: Abu Osman, N.A., Ibrahim, F., Wan Abas, W.A.B., Abdul Rahman, H.S., Ting, HN. (eds) 4th Kuala Lumpur International Conference on Biomedical Engineering 2008. IFMBE Proceedings, vol 21. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69139-6_57
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DOI: https://doi.org/10.1007/978-3-540-69139-6_57
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69138-9
Online ISBN: 978-3-540-69139-6
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